Trend-based projections

Four variants of trend-based population projections and corresponding household projections are currently available to download. These are labelled as High, Central and Low and differ in their domestic migration assumptions beyond 2017. The economic crisis has been linked to a fall in migration from London to the rest of the UK and a rise in flows from the UK to London. The variants reflect a range of scenarios relating to possible return to pre-crisis trends in migration.

High: In this scenario, the changes to domestic migration flows are considered to be structural and recent patterns persist regardless of an improving economic outlook.

Low: Changes to domestic migration patterns are assumed to be transient and return to pre-crisis trends beyond 2018. Domestic outflow propensities increase by 10% and inflows decrease by 6% as compared to the High variant.

Central: Assumes recent migration patterns are partially transient and partially structural. Beyond 2018, domestic outlow propensities increase by 5% and inflows by 3% as compared to the High variant.

Central - incorporating 2012-based fertility assumptions: Uses the same migration assumptions as the Central projeciton above, but includes updated age-specific-fertility-rates based on 2011 birth data and future fertility trends taken from ONS's 2012-based National Population Projections. The impact of these changes is to increase fertility by ~10% in the long term.

GLA 2013 round trend-based population projections:
Borough: High
Borough: Low
Borough: Central
Borough: Central - incorporating 2012-based NPP fertility assumptions
Ward: Central

GLA 2013 round trend-based household projections:
Borough: High
Borough: Low
Borough: Central

GLA 2013 round ethnic group population projections:
Borough: Central

Updates:
Update 03-2014: GLA 2013 round of trend-based population projections - Methodology
Update 04-2014: GLA 2013 round of trend-based population projections - Results
Data to accompany Update 04-2014
Update 12-2014: GLA 2013 round ethnic group population projections
Data to accompany Update 12-2014

Housing linked projections

Two variants of housing-linked projections are available based on housing trajectories derived from the 2013 Strategic Housing Land Availability Assessment (SHLAA). The two variants are produced using different models to constrain the population to available dwellings. These are referred to as the DCLG-based model and the Capped Household Size model. These models will be explained in greater detail in an upcoming Intelligence Unit Update.

Projection Models:

DCLG-Based Model

This model makes use of Household Representative Rates (HRR) from DCLG’s 2011-based household projections to convert populations by age and gender into households. The models uses iteration to find a population that yields a total number of households that matches the number of available household spaces implied by the development data. This iterative process involves modulating gross migration flows between each London local authority and UK regions outside of London. HRRs beyond 2021 have been extrapolated forward by the GLA. The model also produces a set of household projections consistent with the population outputs.

Capped Household Size Model

This model was introduced to provide an alternative projection based on the SHLAA housing trajectories. While the projections given by the DCLG-Based Model appear realistic for the majority of London, there are concerns that it could lead to under projection for certain local authorities, namely those in Outer London where recent population growth has primarily been driven by rising household sizes. For these boroughs, the Capped Household Size model provides greater freedom for the population to follow the growth patterns shown in the Trend-based projections, but caps average household size at 2012 levels. For boroughs where the DCLG-based SHLAA model gave higher results than the Trend-based model, the projections follow the results of the former.

Household projections are not available from this model.

Development assumptions:

SHLAA housing data

These projections incorporate development data from the 2013 Strategic Housing Land Availability Assessment (SHLAA) database to determine populations for 2012 onwards. Development trajectories are derived from this data for four phases: 2015-20, 2021-25, 2026-30, and 2031-36. For 2012-14, data is taken from the 2009 SHLAA trajectories. No data is included in the database for beyond 2036 and the 2031-36 trajectories are extended forward to 2041. This data was correct as at February 2014 and may be updated in future. Assumed development figures will not necessarily match information in the SHLAA report as some data on estate renewals is not included in the database at this time.

GLA 2013 round SHLAA-based population projections:
Borough: SHLAA-based
Borough: capped SHLAA-based
Ward: SHLAA-based
Ward: capped SHLAA-based

GLA 2013 round SHLAA-based household projections:
Borough: SHLAA-based

GLA 2013 round SHLAA-based ethnic group population projections:
Borough: SHLAA-based

Zero-development projections

The GLA produces so-called zero-development projections for London that assume that future dwelling stocks remain unchanged. These projections can be used in conjunction with the SHLAA-based projections to give an indication of the modelled impact of the assumed development. Variants are produced consistent with the DCLG-based and Capped Household Size projections. Due to the way the models operate, the former assumes no development beyond 2011 and the latter no development after 2012.

GLA 2013 round zero development population projections:
Borough: DCLG zero development
Borough: capped zero development
Ward: DCLG zero development
Ward: capped zero development

Frequently asked question: which projection should I use?

The GLA Demography Team recommends using the Capped Household Size SHLAA projection for most purposes. The main exception to this is for work estimating future housing need, where it is more appropriate to use the trend-based projections.

The custom-age population tool is here.

To access the GLA's full range of demographic projections please click here.

Europe Residential Construction Market size was valued at USD 1.08 Trillion in 2024 and is projected to reach USD 1.64 Trillion by 2032, growing at a CAGR of 5.4% from 2026 to 2032.

Europe Residential Construction Market Drivers

Rising Demographic Shifts and Urbanization Trends: The continuous migration to urban centers across Europe is increasing the housing demands, particularly in major metropolitan areas. According to Eurostat’s 2023 data, 75% of the EU population now resides in urban areas, marking a 2.3% increase from the previous year. This urbanization trend has created substantial pressure on residential construction, especially in cities like Berlin, Paris, and Amsterdam, where housing shortages have become increasingly acute.

Growing Sustainable Building Requirements: European nations are witnessing a fundamental shift toward sustainable and energy-efficient housing construction. The European Commission reported in November 2023 that 42% of new residential building permits across the EU now incorporate renewable energy systems. This transformation is driven by stringent environmental regulations, including the EU’s Energy Performance of Buildings Directive, which mandates nearly zero-energy buildings for all new construction.

Escalating Government Housing Initiatives: The European government has intensified its commitment to addressing housing shortages through various support programs and incentives. The German Federal Statistical Office revealed in January 2024 that government spending on residential construction subsidies reached €18.2 billion, representing a 15% increase year-over-year. These initiatives have particularly focused on affordable housing development and first-time homebuyer assistance programs.

Abstract

Over the past decade, Albania has been seeking to develop the framework for a market economy and more open society. It has faced severe internal and external challenges in the interim - extremely low income levels and a lack of basic infrastructure, the rapid collapse of output and inflation rise after the shift in regime in 1991, the turmoil during the 1997 pyramid crisis, and the social and economic shocks accompanying the 1999 Kosovo crisis. In the face of these challenges, Albania has made notable progress in creating conditions conducive to growth and poverty reduction. A poverty profile based on 1996 data (the most recent available) showed that some 30 percent of the rural and some 15 percent of the urban population are poor, with many others vulnerable to poverty due to their incomes being close to the poverty threshold. Income related poverty is compounded by the severe lack of access to basic infrastructure, education and health services, clean water, etc., and the ability of the Government to address these issues is complicated by high levels of internal and external migration that are not well understood. To date, the paucity of household-level information has been a constraining factor in the design, implementation and evaluation of economic and social programs in Albania. Multi-purpose household surveys are one of the main sources of information to determine living conditions and measure the poverty situation of a country and provide an indispensable tool to assist policymakers in monitoring and targeting social programs. Two recent surveys carried out by the Albanian Institute of Statistics (INSTAT) - the 1998 Living Conditions Survey (LCS) and the 2000 Household Budget Survey (HBS) - drew attention, once again, to the need for accurately measuring household welfare according to well accepted standards, and for monitoring these trends on a regular basis. In spite of their narrow scope and limitations, these two surveys have provided the country with an invaluable training ground towards the development of a permanent household survey system to support the government strategic planning in its fight against poverty. In the process leading to its first Poverty Reduction Strategy Paper (PRSP; also known in Albania as Growth and Poverty Reduction Strategy, GPRS), the Government of Albania reinforced its commitment to strengthening its own capacity to collect and analyse on a regular basis the information it needs to inform policy-making. In its first phase (2001-2006), this monitoring system will include the following data collection instruments:

(i) Population and Housing Census (ii) Living Standards Measurement Surveys every 3 years (iii) annual panel surveys.

The Population and Housing Census (PHC) conducted in April 2001, provided the country with a much needed updated sampling frame which is one of the building blocks for the household survey structure. The focus during this first phase of the monitoring system is on a periodic LSMS (in 2002 and 2005), followed by panel surveys on a sub-sample of LSMS households (in 2003, 2004 and 2006), drawing heavily on the 2001 census information. The possibility to include a panel component in the second LSMS will be considered at a later stage, based on the experience accumulated with the first panels. The 2002 LSMS was in the field between April and early July, with some field activities (the community and price questionnaires) extending into August and September. The survey work was undertaken by the Living Standards unit of INSTAT, with the technical assistance of the World Bank. The present document provides detailed information on this survey. Section II summarizes the content of the survey instruments used. Section III focuses on the details of the sample design. Sections IV describes the pilot test and fieldwork procedures of the survey, as well as the training received by survey staff. Section V reviews data entry and data cleaning issues. Finally, section VI contains a series of annotations that all those interested in using the data should read.

Geographic coverage

National

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

(a) SAMPLING FRAME

The Republic of Albania is divided geographically into 12 Prefectures (Prefekturat). The latter are divided into Districts (Rrethet) which are, in turn, divided into Cities (Qyteti) and Communes (Komunat). The Communes contain all the rural villages and the very small cities. For the April 2001 General Census of Population and Housing census purposes, the cities and the villages were divided into Enumeration Areas (EAs). These formed the basis for the LSMS sampling frame. The EAs in the frame are classified by Prefecture, District, City or Commune. The frame also contains, for every EA, the number of Housing Units (HUs), the number of occupied HUs, the number of unoccupied HUs, and the number of households. Occupied dwellings rather than total number of dwellings were used since many census EAs contain a large number of empty dwellings. The Housing Unit (defined as the space occupied by one household) was taken as the sampling unit, instead of the household, because the HU is more permanent and easier to identify in the field. A detailed review of the list of censuses EAs shows that many have zero population. In order to obtain EAs with a minimum of 50 and a maximum of 120 occupied housing units, the EAs with zero population were first removed from the sampling frame. Then, the smallest EAs (with less than 50 HU) were collapsed with geographically adjacent ones and the largest EAs (with more than 120 HU) were split into two or more EAs. Subsequently, maps identifying the boundaries of every split and collapsed EA were prepared Sample Size and Implementation Since the 2002 LSMS had been conducted about a year after the April 2001 census, a listing operation to update the sample EAs was not conducted. However, given the rapid speed at which new constructions and demolitions of buildings take place in the city of Tirana and its suburbs, a quick count of the 75 sample EAs was carried out followed by a listing operation. The listing sheets prepared during the listing operation became the sampling frame for the final stage of selection. The final sample design for the 2002 LSMS included 450 Primary Sampling Units (PSUs) and 8 households in each PSU, for a total of 3600 households. Four reserve units were selected in each sample PSU to act as replacement unit in non-response cases. In a few cases in which the rate of migration was particularly high and more than four of the originally selected households could not be found for the interview, additional households for the same PSU were randomly selected. During the implementation of the survey there was a problem with the management of the questionnaires for a household that had initially refused, but later accepted, to fill in the food diary. The original household questionnaire was lost in the process and it was not possible to match the diary with a valid household questionnaire. The household had therefore to be dropped from the sample (this happened in Shkoder, PSU 16). The final sample size is therefore of 3599 households.

(b) STRATIFICATION

The sampling frame was divided in four regions (strata), Coastal Area, Central Area, and Mountain Area, and Tirana (urban and other urban). These four strata were further divided into major cities, other urban, and other rural. The EAs were selected proportionately to the number of housing units in these areas. In the city of Tirana and its suburbs, implicit stratification was used to improve the efficiency of the sample design. The implicit stratification was performed by ordering the EAs in the sampling frame in a geographic serpentine fashion within each stratum used for the independent selection of EAs.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

(a) QUALITY CHECKS Besides the checks built-in in the DE program and those performed on the preliminary versions of the dataset as it was building up, and additional round of in depth checks on the household questionnaire and the food diary was performed in late September and early October in Tirana. Wherever possible data entry errors or inconsistencies in the dataset were spotted, the original questionnaires or diary were retrieved, and the information contained therein checked. Changes were made to the August version of the dataset as needed and the dataset was finalized in October.

(b) DATA ENTRY Data Entry Operations Data entry for all the survey instruments was performed using custom made applications developed in CS-Pro. Data entry for the household questionnaire was performed in a decentralized fashion in parallel with the enumeration, so as to allow for 'real-time' checking of the data collected. This allowed a further tier of quality control checks on the data. Where errors in the data were spotted during data entry, it was possible to instruct enumerators and supervisors to correct the information, if necessary, revisiting the household, when the teams were still in the field. A further round of checks was performed by the core team in Tirana and Bank staff in Washington as the data were gathered from the field and the entire dataset started building up. All but one of the 16 teams in the districts had one DEO, the Fier team had two, and there were four DEO's for Tirana. Each DEO worked with a laptop computer, and was given office space in the regional Statistics Offices, or in INSTAT headquarters for the Tirana teams. The DEO's received Part 1 of the household questionnaire from the supervisor once the supervisor had checked the enumerator's work, within two